*Our apologies if you receive multiple copies of this announcement*
 
Call for papers: CEC2008 (@WCCI2008) Special Session on Large Scale
Global
Optimization http://nical.ustc.edu.cn/cec08ss.php    
 
 
In the past two decades, different kinds of nature-inspired optimization
algorithms have been designed and applied to solve optimization
problems,
e.g., simulated annealing (SA), evolutionary algorithms (EAs),
differential
evolution (DE), particle swarm optimization (PSO), Ant Colony
Optimisation
(ACO), Estimation of Distribution Algorithms (EDA), etc. Although these
approaches have shown excellent search abilities when applying to some
30-100 dimensional problem, many of them suffer from the "curse of
dimensionality", which implies that their performance deteriorates
quickly
as the dimensionality of search space increases. The reasons appear to
be
two-fold. First, complexity of the problem usually increases with the
size
of problem, and a previously successful search strategy may no longer be
capable of finding the optimal solution. Second, the solution space of
the
problem increases exponentially with the problem size, and a more
efficient
search strategy is required to explore all the promising regions in a
given
time budget. 
 
Historically, scaling EAs to large size problems have attracted much
interest, including both theoretical and practical studies. The earliest
practical approach might be the parallelism of an existing EA. Later,
cooperative coevolution appears to be another promising method. However,
existing work on this topic are often limited to the test problems used
in
individual studies, and a systematic evaluation platform is not
available in
the literature for comparing the scalability of different EAs.
 
This special session is devoted to the novel approaches, algorithms and
techniques for tackling large scale global optimization problems,
involving
single objective or multiple objectives, binary or discrete or real or
mixed
variables. Papers on novel test suites that help us in understanding
problem
characteristics are also welcome. We encourage all authors to submit
their
test functions, algorithms and results to the Birmingham Benchmark site
---
Evolutionary Computation Benchmark Repository (EvoCoBR):
http://www.cs.bham.ac.uk/research/projects/ecb/ .

Further, a set of scalable function optimization problems are available
at: http://nical.ustc.edu.cn/cec08ss.php . Authors working on numerical
optimizations are encouraged to test their algorithms on the test suite.
We will archive the comparative results as we did during the CEC 2005,
2006 & 2007 at http://www.ntu.edu.sg/home/epnsugan .

All papers accepted by the special session will be included in the
CEC'08
conference proceedings and selected authors will be invited to present
their
results during WCCI-08.
 
Special session organizers:
 
Ke Tang
Nature Inspired Computation and Applications Laboratory (NICAL), 
University of Science and Technology of China, Hefei, Anhui, China
 
P. N. Suganthan
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore
 
Xin Yao
Nature Inspired Computation and Applications Laboratory (NICAL), 
University of Science and Technology of China 
 
The Centre of Excellence for Research in Computational Intelligence and
Applications (CERCIA), 
The University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
 
Cara MacNish 
School of Computer Science & Software Engineering 
The University of Western Australia

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A/Prof P N Suganthan                   Tel: 65 6790 5404
School of EEE                          Fax: 65 6792 0415
Nanyang Technological University       [log in to unmask]   
Republic of Singapore 639798           Office: S2-B2a-21
http://www.ntu.edu.sg/home/epnsugan   
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